Memorial University DAI: A bottom-up approach for XML document classification

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Document Description

Title	A bottom-up approach for XML document classification
Author	Wu, Junwei.
Description	Thesis (M.Sc.)--Memorial University of Newfoundland, 2009. Computer Science
Date	2009
Pagination	viii, 64 leaves : ill.
Subject	Data mining; XML (Document markup language)--Classification;
Degree	M.Sc.
Degree Grantor	Memorial University of Newfoundland. Dept. of Computer Science
Discipline	Computer Science
Language	Eng
Notes	Includes bibliographical references (leaves 61-64)
Abstract	Extensible Markup Language (XML) is a simple and flexible text format derived from Standard Generalized Markup Language (SGML) [1]. It has been widely accepted as a crucial component of many information retrieval related applications, such as XML databases, web services, etc. One of the reasons for its wide acceptance is its customized format during data transmission or storage. Classification is an important data mining task that aims to assign unknown objects to classes that best characterize them. In this thesis, we propose a method to classify XML documents under the assumption that they do not have a common schema that may or may not be available, which is closer to the real cases. Our method is similarity-based. Its main characteristic is its way to handle the roles played by texts and the structural information. Unlike most existing methods, we use a bottom-up approach, i.e., we start from the text first, and then embed the structural information. This is based on the observation that in XML documents with diversified tag structures, the most informative information is carried by the terms in the texts. Our experiments show that this strategy can achieve a better performance than the existing methods for documents from sources that exhibit heterogeneous structures.
Type	Text
Resource Type	Electronic thesis or dissertation
Format	Image/jpeg; Application/pdf
Source	Paper copy kept in the Centre for Newfoundland Studies, Memorial University Libraries
Local Identifier	a3243873
Rights	The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.
Collection	Electronic Theses and Dissertations
Scanning Status	Completed
PDF File	(8.26 MB) -- http://collections.mun.ca/PDFs/theses/Wu_Junwei.pdf
CONTENTdm file name	41293.cpd